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Bifurcations in a delayed fractional complex-valued neural network

  • Chengdai Huang
  • , Jinde Cao
  • , Min Xiao
  • , Ahmed Alsaedi
  • , Tasawar Hayat
  • Southeast University, Nanjing
  • Faculty of Sciences, King Abdulaziz University
  • Nanjing University of Posts and Telecommunications
  • Quaid-I-Azam University

Research output: Contribution to journalArticlepeer-review

148 Scopus citations

Abstract

Complex-valued neural networks (CVNNs) with integer-order have attracted much attention, and which have been well discussed. Fractional complex-valued neural networks (FCVNNs) are more suitable to describe the dynamical properties of neural networks, but have rarely been studied. It is the first time that the stability and bifurcation of a class of delayed FCVNN is investigated in this paper. The activation function can be expressed by separating into its real and imaginary parts. By using time delay as the bifurcation parameter, the dynamical behaviors that including local asymptotical stability and Hopf bifurcation are discussed, the conditions of emergence of bifurcation are obtained. Furthermore, it reveals that the onset of the bifurcation point can be delayed as the order increases. Finally, an illustrative example is provided to verify the correctness of the obtained theoretical results.

Original languageEnglish
Pages (from-to)210-227
Number of pages18
JournalApplied Mathematics and Computation
Volume292
DOIs
StatePublished - 1 Jan 2017
Externally publishedYes

Keywords

  • Complex-valued
  • Fractional neural networks
  • Hopf bifurcation
  • Stability
  • Time delays

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